Title :
Lossless Hyperspectral-Image Compression Using Context-Based Conditional Average
Author :
Wang, Hongqiang ; Babacan, S. Derin ; Sayood, Khalid
Author_Institution :
Nebraska-Lincoln Univ., Lincoln
Abstract :
In this paper, a new algorithm for lossless compression of hyperspectral images is proposed. The spectral redundancy in hyperspectral images is exploited using a context-match method driven by the correlation between adjacent bands. This method is suitable for hyperspectral images in the band-sequential format. Moreover, this method compares favorably with the recent proposed lossless compression algorithms in terms of compression, with a lower complexity.
Keywords :
geophysical techniques; image coding; remote sensing; band-sequential format; compression algorithms; context-based conditional average; context-match method; lossless hyperspectral-image compression; spectral redundancy; Compression algorithms; Entropy; Humans; Hyperspectral imaging; Hyperspectral sensors; Image coding; NASA; Optimization methods; Planets; Predictive coding; Conditional average; Golomb–Rice code; context coding; correlation; entropy code; hyperspectral image; image coding;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2007.906085
